The Four Phases of Simulation

Data-driven simulations offer a valuable way to minimize your risk when developing advanced automated solutions. By mimicking real-life performance with a high degree of accuracy, these computer-based models can help ensure that your system will meet your requirements and expectations before you even begin building it. Simulation can also play a role during the engineering phase by testing multiple scenarios, helping your system meet new requirements, identifying potential pitfalls in the design, and ensuring smoother implementation.

The simulation process typically takes place in four phases. Here’s what happens in each and what you can expect your role to be at each stage of the process.

1.       Pre-modeling

Accurate data and clearly defined expectations are critical to the success of any simulation project. So before any modeling begins, you’ll meet with experienced engineers from the Operations and Solutions Development (OSD) team. During the initial kickoff meeting, they’ll work with you to define the desired performance of your system and the goals of the simulation. Together, you’ll determine the scope of the project and agree on any clarifications and assumptions needing consideration.

Although your simulation can be built with generic order profiles based on probabilities, it’s best if you can provide actual data specific to your goals. Actual data will be beneficial for several reasons. First, you know your operation’s facts and figures better than anyone; more accurate data leads to more accurate simulations. Your data can also alert the OSD team to variables your simulation needs to consider. For example, your overall throughput rate might be calculated per hour, but that might be deceiving as your facility might process orders in waves versus a constant rate. We can accommodate such variables in simulated workflows.

2.       Model Building

Once the customer and OSD establish the simulation goals and accurate data gathered, the OSD team goes to work coding the simulation models and creating a visual representation of your system. When the development of these elements is complete, the project team will collaborate with you to identify any errors or corrections to the simulation. Together you’ll confirm and agree upon any assumptions. Any last-minute updates to the simulation model are done at this time.

The end product of this second phase is a simulation model that establishes the baseline used as a control in the following stages.

3.       Model Runs

In the third phase, the OSD team begins running the simulation. Various throughputs and outputs are examined, interpreted, and documented.

This stage aims to pinpoint any potential problems in the system, such as throughputs, bottlenecks, or utilization challenges. These findings are collated into a detailed simulation report that summarizes the team’s results and conclusions.

4.       Experimentation

One of the most valuable functions of any simulation is the ability to run “what-if” scenarios or experiments. These alternative models run significantly faster than the real-time performance of your system, enabling you to test options very quickly.

Each experiment tweaks the properties of the base model to find potential performance enhancements and identify potential pitfalls. For example, you can adjust the time it takes an operator to complete a task, how much product is introduced at a time, the speed of a conveyor, a sensitivity analysis of the quantity of autonomous mobile robots (AMRs) in the system, or the number of locations available to store product. The results of these scenarios can then be compared to the base model and any other promising iterations that appear along the way.

Examining the results of these experiments enables the OSD team to identify the best solution based on the parameters used. Although the number of scenarios required to achieve optimal results can vary considerably depending on the size and complexity of a system, simulation can significantly reduce the time needed to find the ideal combination of factors under consideration.

Final Thoughts

Using simulation in the design and engineering of your system gives your operation a significant competitive advantage that can reduce your risks, enhance your bottom line, enabling faster return on investment (ROI) and increasing customer satisfaction. Knowing where your layout might create bottlenecks and having the ability to test different solutions before you begin installation can also be huge wins for your operation.

To learn more, visit the Solutions Development and Consulting page. There, you’ll find details on how the OSD team can collaborate with you to develop advanced automation strategies for greenfield or brownfield sites while helping you find the best-fit solution for your unique requirements.

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